Apologies for cross-posting
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SUBMISSION DEADLINE: 8. April, 2013
EMPIRE 2013 - 1st workshop on "Emotions and Personality in Personalized
Services, 10. June 2013" http://empire2013.wordpress.com
in conjuction with UMAP 2013 (Rome, Italy) http://www.umap2013.org
Invited speaker: Neal Lathia (University of Cambridge)
http://www.cl.cam.ac.uk/~nkl25/
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While a lot of discussion has been made on filtering algorithms, and
evaluation measures, few studies have stood to consider the role of
emotions and personality in user models and personalized services.
Characterizing the user model and the whole user experience with
personalized service, by means of affective traits, is an important
issue which merits attention from researchers and practitioners in both
web technology and human factor fields.
Some questions motivate this workshop:
- Do affective traits (personality, emotions, and mood) influence and
determine the acceptance of the personalized suggestions?
- How personality traits should be included in the user model?
- How the personalized services should be adapted to emotions and mood
to increase user satisfaction?
SUBMISSION INSTRUCTIONS
=======================
We accept two kinds of submissions: (i) full papers (up to 12 pages) and
(ii) short papers (up to 6 pages). Submissions should be made through
the EasyChair conference system:
https://www.easychair.org/conferences/?conf=empire2013)
and must adhere to the Springer LNCS format
(http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0). All the
submissions will be peer-reviewed. The accepted papers will be published
in a centralized CEUR-WS volume of workshop papers and conference posters.
Further information can be found on the workshop's web page
http://empire2013.wordpress.com
IMPORTANT DATES
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8. April 2013 Paper submission deadline
1. May 2013 Notification of acceptance
10. June 2013 Workshop day
ORGANIZING COMMITTEE
====================
Marko Tkalčič, Johannes Kepler University, Linz, Austria
Berardina De Carolis, University of Bari Aldo Moro, Italy
Marco de Gemmis, University of Bari Aldo Moro, Italy
Ante Odić, University of Ljubljana, Slovenia
Andrej Košir, University of Ljubljana, Slovenia
PROGRAM COMMITTEE
==================================
Alessandro Vinciarelli, University of Glasgow
Aleksander Valjamae, University of Graz
Elisabeth Andre, Augsburg University
Floriana Grasso, Univ. Liverpool
Francesco Ricci, Free University of Bozen-Bolzano
Gustavo Gonzalez, http://goo.gl/tjDx0
Ioannis Arapakis, Yahoo! Barcelona
Jennifer Golbeck, University of Maryland
Judith Masthoff, University of Aberdeen
Li Chen, Hong Kong Baptist University
Man-Kwan Shan, National Chengchi University, Department of Computer Science
Marius Kaminskas, Free University of Bolzano
Martijn Willemsen, Eindhoven University of Technology, Netherlands
Markus Zanker, University Klagenfurt, Austria
Michal Kosinski, Microsoft
Mohammad Soleymani, Univ. Geneva/Imperial college
Neal Lathia, Cambridge University
Rong Hu , EPFL
ABSTRACT
========
In the pursuit of increasing the quality of personalized services,
researchers started to turn to more user-centric descriptors of content
and services in recent years. The advances made in affective computing,
especially in automatic emotion detection techniques, paved the way for
the exploitation of emotions and personality as descriptors that account
for a larger part of variance in user behavior than the generic
descriptors (e.g. genre of a multimedia content) used so far.
Emotions, users' responses, can be characterized in different ways. The
two most common approaches are (i) the discrete basic emotions (discrete
classes, e.g. joy, sadness, fear, disgust, surprise, anger) and (ii) the
continuous values, in the valence-arousal-dominance space. The affective
computing community has been very active in the past decade and has
developed several methods for the automatic non-invasive detection of
emotions via several modalities (Zeng et al., 2009).
While emotions can change pretty quickly, personality, on the other
hand, describes long-lasting human traits. The most common way of
describing personality is the five-factor model (openness,
conscientiousness, extraversion, agreeableness and neuroticism).
Emotions and personality in personalized services (e.g., recommender
systems) can be exploited in different ways at different stages in the
service-usage (e.g. content consumption) chain (Tkalčič et. al, 2011).
In the entry stage they can be used as a contextual parameter, as
additional information to predict, assist and influence decision-making
(Kahneman, 2011) or a way to diversify the personalization via the
detection of serendipitous services. In the consumption stage, emotions
can be used as additional tags for the characterization of the services,
content and users (Jiao and Pantid, 2011), opening new research areas
for modeling services and content with different lengths. Finally,
emotions can be exploited also for the non-invasive acquisition of the
implicit user feedback as well as for novel evaluation metrics.
So far, research on emotions and personality in personalized services
has been carried out in a scattered fashion. The goal of this workshop
is to provide a venue for researchers to present their work, discuss it
and benefit from the interaction.
TOPICS
======
- Affective modeling
- Emotions as context
- Emotions in the decision-making process for recommender systems
- Role of personality on user similarities
- Emotion detection in recommended content consumption
- Emotion detection as non-invasive feedback
- Affective tagging of multimedia content and services
- Emotion-based evaluation metrics (satisfaction...)
- Lifestyle recommender systems
- Personality and mood for group decision making
- Incorporating personality and emotions in user models
- Models based on personality
- Datasets for affective modeling (Collecting, Available)
- Personality traits acquisition (explicit vs. implicit)
- Assessing personality traits implicitly from users’
activities/ratings/behavior
- Personality and interfaces/control/bubble-control
- Could interfaces/control/bubble-control be personalized based on
personality traits? Should they be?
- Personality and users’ tasks/goals
- Do personality traits influence users’ goals?
- Social signal processing for personalized services
- Strategies for modeling emotions and personality
- Recognizing triggers and causes of emotion
- Theories about the relationship between reasoning and affect, between
decision-making and affect
- Methods for evaluating the utility of adaptation to affective factors
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Dr. Marko Tkalcic
http://markotkalcic.wordpress.com
Skype : markotkalcic
Twitter:https://twitter.com/#!/RecSysMare
Linkedin:http://www.linkedin.com/in/markotkalcic
Google Scholar:http://scholar.google.com/citations?user=JQ2puysAAAAJ
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